Classification of lung nodules in diagnostic CT: An approach based on 3-D vascular features, nodule density distributions, and shape features

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5032 I, Issue , 2003, Pages 183-189

  Lo, Shih Chung B ^a   Hsu, Li Yueh ^b   Freedman, Mathew T ^a   Lure, Y M Fleming ^c   Zhao, Hui ^a,d  

^a GEORGETOWN UNIVERSITY MEDICAL CENTER   (United States)

^b NATIONAL HEART LUNG AND BLOOD INSTITUTE   (United States)

^c Deus Technologies Inc   (United States)

^d CATHOLIC UNIVERSITY OF AMERICA   (United States)

Author keywords

Computer aided diagnosis; Lung cancer; Pattern recognition; Vascular features

Indexed keywords

BACKPROPAGATION; COMPUTER AIDED DIAGNOSIS; ENTROPY; NEURAL NETWORKS; PATTERN RECOGNITION; PULMONARY DISEASES;

LUNG NODULES;

COMPUTERIZED TOMOGRAPHY;

EID: 0042376076     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.481878     Document Type: Conference Paper

References (11)

1. Henschke C.I., McCauley D.I., Yankelevitz D.P., McGuinness G.; Miettinen O.S., Libby, D.M., Pasmantier M.W., Koizumi J., Altorki N.K., Smith J.P., Early Lung Cancer Action Project: overall design and findings from baseline screening. The Lancet- 354; 9173: 99-105, 1999.
2. Sone S., Shodayu T., Feng L., et al. Mass Screening for Lung Cancer with Mobil Spiral Computed Tomography Scanner, The Lancet, Vol 351, pp 1242-1245, 1998.
3. Zerhouni E.A., Stitik F..P, Siegelman S.S., et al: CT of Pulmonary Nodule: A Coorporative Study. Radiology 160:319-327, 1986.
4. Siegelman S.S., Khouris N.F., Leo F.P., et al: Solitary Pulmonary Nodules: CT Assessment. Radiology 160: 307-312, 1986.
5. Zerhouni E.A., Spivey J.F., et al: Factors Influencing Quantitative CT Measurements of Solitary Pulmonary Nodules. J Comput Assist Tomogr 6:1075-1087, 1982.
6. Webb W.R.,: Radiologic Evaluation of the Solitary Pulmonary Nodule. AJR Am J Roentgenol 154:701-708, 1990.
7. Zwirewich C.V., Vedal S., Miller R.R., Muller N.L., Solitary Pulmonary Nodule: High-Resolution CT and Radiologic-Pathologic Correlation, Radiology, 179: 469-476, 1991.
8. Zhao B., Yankelevitz D., Reeves A., and Henschke C., Two-dimensional Multi-criterion Segmentation of Pulmonary Nodules on Helical CT Images, Med. Phys., 26, pp. 889-895, 1999.
9. Delegacz A.M., Lo S.C., Xei H.C., Freedman M.T., and Mun S.K. "3D Visualization and Tumor-Vascularity Analysis of Lung Features in Volumetric CT Lung Cancer Diagnosis" SPIE Med. Imag., vol. 4319, 2001.
10. Wei D., Chan H.P., Helvie M.A., Sahiner B., Patrick N., Adler D.D., and Goodsitt MM: Calssification of mass and normal breast tissue on digital mammograms: Multiresoltion texture analysis, Medical Physics 1995.vol, 22(9):1501-1513.
11. Kinnard L., Lo S-C. B., Wang P., Freedman M.T., Chouikha M., "Separation of Malignant and Benign Masses using a Maximum-Likelihood Analysis and Neural Networks," SPIE Med. Imag. Vol. 4684, 733-741, 2002.